Machine translation is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another. On a basic level, machine translation performs simple substitution of words in one language for words in another language, but that alone usually cannot produce a good translation of text because recognition of whole phrases and their closest counterparts in the target language is needed.
Current machine translation techniques are relatively ineffective at producing accurate and reliable translations. One problem is that the training corpus upon which a machine translator is based is extremely limited, even if the training corpus is relatively large in size. The variation in how ideas and concepts may be expressed in a given language is so great that it is nearly impossible for a machine translator to generate accurate translations, unless the phrases that need translating appear word-for-word in the training corpus. For example, many English-to-Chinese machine translators of free form text have a sub 20% accuracy rate.
The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.